DP4848 On the Fit and Forecasting Performance of New Keynesian Models

Author(s): Marco Del Negro, Frank Schorfheide, Frank Smets, Rafael Wouters
Publication Date: January 2005
Keyword(s): Bayesian Analysis, DSGE models, model evaluation, vector autoregression
JEL(s): C11, C32, C53
Programme Areas: International Macroeconomics
Link to this Page: cepr.org/active/publications/discussion_papers/dp.php?dpno=4848

The Paper provides new tools for the evaluation of DSGE models, and applies it to a large-scale New Keynesian dynamic stochastic general equilibrium (DSGE) model with price and wage stickiness and capital accumulation. Specifically, we approximate the DSGE model by a vector autoregression (VAR), and then systematically relax the implied cross-equation restrictions. Let delta denote the extent to which the restrictions are being relaxed. We document how the in- and out-of-sample fit of the resulting specification (DSGE-VAR) changes as a function of delta. Furthermore, we learn about the precise nature of the misspecification by comparing the DSGE model?s impulse responses to structural shocks with those of the best-fitting DSGE-VAR. We find that the degree of misspecification in large-scale DSGE models is no longer so large to prevent their use in day-to-day policy analysis, yet it is not small enough that it cannot be ignored.